Autonomous construction framework for crane control with enhanced soft actor–critic algorithm and real-time progress monitoring
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
With the shortage of skilled labors, there is an increasing demand for automation in the construction industry. This study presents an autonomous construction framework for crane control with enhanced soft actor–critic (SAC-E) algorithm and real-time progress monitoring. SAC-E is a novel reinforcement learning algorithm with superior learning speed and training stability for lifting path planning. In addition, robotic kinematics and a control algorithm are implemented to ensure that the crane can autonomously execute the lifting path. Last, novel hardware communication interfaces between robot operating system and building information modeling (BIM) are developed for real-time construction progress monitoring. The performance of the proposed framework was demonstrated using a robotized mobile crane to stack concrete retaining blocks. The results show that the proposed framework can be effectively used to execute the retaining block construction using the robotized mobile crane with real-time construction update in the BIM platform.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it